Founded in 1971, the Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly innovative applications pertaining to the analysis and interpretation of multidimensional data.
The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including cluster analysis, discriminant analysis, factor analysis, and multidimensional continuous or discrete distribution theory. Topics of current interest include, but are not limited to, inferential aspects of
Copula modeling
Functional data analysis
Graphical modeling
High-dimensional data analysis
Image analysis
Multivariate extreme-value theory
Sparse modeling
Spatial statistics
Papers making substantial contributions to regression or time series analysis for multidimensional response variables are also invited. Submissions dealing with univariate models, including regression models with a single response variable and univariate time series models, are deemed to fall outside the journal's remit. 
JMVA is particularly interested in papers motivated by, and fit for, contemporary multivariate data analytic challenges. Methods should be validated through standard mathematical arguments that may be complemented with asymptotic arguments or computer-based experiments. Illustrations with relevant, original data are strongly encouraged when presented with clear contextual justification and explanation. 
Papers whose content is probabilistic in nature or whose main contribution is to substantive areas (e.g., actuarial science, biostatistics, economics, finance or hydrology) typically fall outside the journal's scope and will only be considered for publication if the statistical methodology used is both novel and broadly applicable. Finally, note that contributors to multivariate survival analysis, reliability theory and statistical quality control should submit their papers to journals specializing in these areas to ensure that their work reaches the targeted audience.

Editor-in-Chief
Dietrich von Rosen
Swedish University of Agricultural Sciences, Uppsala, Sweden
Executive Editor
Tonu Kollo
University of Tartu, Tartu, Estonia
Associate Editors
Makoto Aoshima
University of Tsukuba Graduate School of Pure and Applied Sciences Doctoral Program in Mathematics, Tsukuba, Japan Classification and discrimination methods; High-dimensional data analysis; Principal component analysis
Adelchi Azzalini
University of Padua, Padova, Italy Density-based non-parametric cluster analysis; Likelihood-based inference; Longitudinal data analysis; Multivariate distribution theory; Non-parametric estimation via smoothing methods
Taras Bodnar
Stockholm University, Stockholm, Sweden Bayesian statistics, Copula modeling, High-dimensional statistics, Multiple testing
Prabir Burman
University of California Davis, Davis, California, United States Asymptotic theory, Discrete data, Nonparametric function estimation, Resampling methods, Spatial statistics, Spatio-temporal statistics, Time series
Kehui Chen
University of Pittsburgh, Pittsburgh, Pennsylvania, United States Functional and longitudinal data analysis, Multilevel clustering,Multilevel correlation analysis, Network analysis,Applications in brain functional connectivity
Ratan Dasgupta
Indian Statistical Institute, Kolkata, India Advanced applied multivariate analysis
Liliana Forzani
National University of the Littoral Faculty of Chemical Engineering, Sante Fe, ArgentinaCasual inference; High-dimensional data analysis; Multivariate linear models; Multivariate generalized linear models; Sufficient dimension reduction
Christian Genest
McGill University, Montréal, Quebec, Canada Copula modeling, Extreme-value theory, Multivariate distributions, Rank-based inference
Stéphane Girard
Inria Research Centre Grenoble Rhône-Alpes, Montbonnot St Martin, FranceClassification and discrimination methods; Copulas; Extreme value inference; High-dimensional data analysis
Solomon Harrar
University of Kentucky, Lexington, Kentucky, United States Asymptotic theory; High-dimensional data analysis; Multivariate distribution theory; Rank based methods
Thomas Holgersson
Linnaeus University Department of Economics and Statistics, Växjö, Sweden Descriptive multivariate analysis; High-dimensional data analysis; Regularization methods; Multivariate autokorrelation
Jianhua Hu
Shanghai University of Finance and Economics, Shanghai, China Compositional data analysis; High-dimensional data analysis; Sparse statistical modelling; Spatial statistics
Jianhua Huang
Texas A&M University College Station, College Station, Texas, United States Functional data analysis; Graphical models; High-dimensional data analysis; Sparse statistical modelling; Spatial statistics
Harry Joe
The University of British Columbia, Vancouver, British Columbia, Canada Composite likelihood; Copulas; Dependence measures; Extreme value inference; Latent variable models; Multivariate random effects models.
John Kent
University of Leeds, Leeds, United Kingdom Directional statistics; Shape analysis
Yuriy Kharin
Belarusian State University, Minsk, Belarus Classification and discrimination methods; Robust multivariate methods
Bernhard Klar
Helmholtz Nuclear Research Centre Karlsruhe, Karlsruhe, Germany Classification and discrimination methods; Copulas; Multivariate distribution theory
Ivan Kojadinovic
University of Pau and Pays de l’Adour, Pau, France Copulas, Change-point detection, Resampling techniques, Empirical processes, Non-parametric multivariate analysis, Environmental and financial applications
Piotr Kokoszka
Colorado State University, Fort Collins, Colorado, United States Extreme value inference; Functional data analysis; Spatial statistics
Runze Li
Pennsylvania State University, University Park, Pennsylvania, United States Feature screening methods; High-dimensional data analysis; Longitudinal data analysis
Yehua Li
University of California Riverside, Riverside, California, United States Functional data analysis; High-dimensional data analysis; Longitudinal data analysis, Spatial-temporal statistics
Shuangzhe Liu
University of Canberra Faculty of Education Science and Technology Multivariate distributions; multivariate linear models and GLM; statistical diagnostics
Yufeng Liu
University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United StatesClassification and discrimantion methods; Clustering methods; Graphical models; High-dimensional data analysis; Individualized decision rules; Sparse statistical modelling
Richard Lockhart
Simon Fraser University, Burnaby, British Columbia, Canada
Eric Marchand
University of Sherbrooke, Sherbrooke, Quebec, Canada Bayesian methods; Estimation with constraints; Multivariate distribution theory; Parametric inference; Stein estimation
Thomas Mathew
University of Maryland Baltimore, Baltimore, Maryland, United States General multivariate statistical analysis; Mixed and random effects models
Paul McNicholas
McMaster University, Hamilton, Ontario, Canada
Alexander Meister
University of Rostock, Rostock, Germany Functional data analysis, Non-parametric curve estimation, Le Cam theory of statistical experiments, Statistical inverse problems
Sayan Mukherjee
Duke University, Durham, North Carolina, United States Bayesian methods, Geometry and topology in statistical inference, Statistical genetics, Statistical machine learning
Jamal Najim
University Paris-Est Créteil Val de Marne, Creteil, France High-dimensional data analysis; Large random matrix theory
Johanna G. Nešlehová
McGill University, Montréal, Quebec, Canada Copula modeling, Extreme-value theory, Multivariate distributions, Rank-based inference
Natalie Neumeyer
University of Hamburg, Hamburg, Germany Multivariate bootstrap methods; Non-parametric multivariate analysis; Semi-parametric multivariate analysis.
Klaus Nordhausen
TU Wien University, Wien, Austria Blind source separation methods; Dimension reduction; Robust multivariate methods
Haruhiko Ogasawara
Otaru University of Commerce, Otaru, Japan Asymptotic theory; Factor analysis; Multivariate skewness and kurtosis measures; Principal component analysis
Jianxin Pan
The University of Manchester, Manchester, United Kingdom Classification and discrimination methods; High-dimensional data analysis; Network analysis; Multivariate distributions; Patterned covariance matrix analysis
Leandro Pardo
Complutense University of Madrid, Madrid, Spain Analysis of multi-way tables; Asymptotic theory; Minimum distance estimators; Robust multivariate methods
Junyong Park
University of Baltimore, Baltimore, Maryland, United States Classification and discrimination methods; Clustering methods; Hypotheses testing in high dimensions; Multiple comparisons.
Wolfgang Polonik
University of California Davis, Davis, California, United States Non-parametric multivariate analysis; Network Analysis; Shape constrained inference; Topological data analysis
Jörg Polzehl
Weierstrass Institute for Applied Analysis and Stochastics, Berlin, GermanyComputational statistics, Functional data analysis, Neuroimaging, Sparse modelling
Matthew Reimherr
Pennsylvania State University, University Park, Pennsylvania, United States Applications in genetics and public health; Functional data analysis, High-dimensional data analysis, Longitudinal data analysis, Nonparametric regression, Shape analysis
Anne Ruiz-Gazen
Toulouse School of Economics, Toulouse, France Computational statistics; Covariance estimation; Outlier detection; Robust statistics; Survey sampling
Wolfgang Schmid
European University Viadrina
Takashi Seo
Tokyo University of Science, Tokyo, Japan Asymptotic theory; Missing data analysis; Multivariate distribution theory
Ali Shojaei
University of Washington, Seattle, Washington, United States Graphical models; Analysis of time series and panel data; High-dimensional data analysis; Network analysis; Statistical aspects of machine learning
Peter X.K. Song
University of Michigan, Ann Arbor, Michigan, United States Dependence modeling, Estimating functions, High-dimensional data analysis, Longitudinal data analysis, Meta analysis
Akimichi Takemura
Shiga University, Hikone, Japan Algebraic methods in multivariate analysis; Decision theory; Multivariate distribution theory
Thomas Verdebout
ULB, Bruxelles, Belgium Asymptotic theory; Directional statistics; High-dimensional data analysis; Rank based multivariate methods
Marlos Viana
University of Illinois at Chicago, Chicago, Illinois, United States Combined multivariate analysis; Complex multivariate analysis; Symmetry analysis of multivariate data.
Philippe Vieu
Paul Sabatier University, Toulouse, France Functional data analysis; Non-parametric multivariate analysis; Semi-parametric multivariate analysis; Sparse statistical modelling
Julia Volaufova
Louisiana State University Health Sciences Center Human Development Center, New Orleans, Louisiana, United States Longitudinal data analysis; Mixed and random effects models; Multivariate linear models
Jianfeng Yao
University of Hong Kong, Pokfulam, Hong Kong High-dimensional data analysis; Large sample covariance matrices; Random matrix theory
Xianyang Zhang
Texas A&M University System, College Station, Texas, United States High dimensional data analysis, Mutlivariate time series analysis
Shurong Zheng
Northeast Normal University, Changchun, China Constrained statistical inference, High dimensional tests, Large dimensional random matrix theory
Liping Zhu
Renmin University of China, Beijing, China Dependence measures; Dimension reduction; Feature screening
Konstantinos Zografos
University of Ioannina, Ioannina, Greece Classification and discrimination methods; Copulas; Discrete multivariate methods; Dependence measures; Multivariate distribution theory; Statistical distances
Advisory Board
H. Chernoff
Harvard University, Cambridge, Massachusetts, United States
D.R. Cox
University of Oxford, Oxford, United Kingdom
D.A.S. Fraser
University of Toronto, Toronto, Ontario, Canada
C. Genest
McGill University, Montréal, Quebec, Canada
C.R. Rao
Pennsylvania State University, University Park, Pennsylvania, United States
Founded and Edited by
P.R. Krishnaiah
1971 - 1988
Chief Editors
C.R. Rao
1988 - 1992
B.C. Arnold
1993 - 1997
J. de Leeuw
1998-2015
C. Genest
2015 - 2019
Publisher
D. Sugrue